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Record W3215178179 · doi:10.1163/18760759-42020005

The ‘Grotian Style’ in International Criminal Justice

2021· article· en· W3215178179 on OpenAlexaff
Frédéric Megret

Bibliographic record

VenueGrotiana · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Law and Human Rights
Canadian institutionsMcGill University
Fundersnot available
KeywordsCognitive reframingInternational lawHubrisLawInternational communityContext (archaeology)Criminal justiceStyle (visual arts)Economic JusticePolitical sciencePublic international lawSociologyPsychologyPoliticsHistory

Abstract

fetched live from OpenAlex

Abstract This article envisages how one might conceptualize the ‘Grotian Style’ in international criminal justice as a practice of adaptation spearheaded by international judges rather than as actual changes occurring in the international system. It foregrounds the emblematic career of Antonio Cassese at the ICTY as epitomizing the trajectory of a scholar on the bench intent on seizing a historic opportunity to reframe the law. The contours, origins, and prospects but also limitations of the ‘Grotian style’ are then discussed. The problem with the Grotian style is not primarily that it runs roughshod over defense rights, but that it appropriates a law-making authority which, in the international system, is better understood as primarily vested in states. In the process, it risks exposing its hubris and shallowness, especially when deciding on normatively intractable issues. In a context where international criminal justice is increasingly being normalized, the time may have come to reconceptualize judges’ role along more global constitutional lines as rooted in an ongoing dialogue with the international community of states and an emerging separation of powers.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.009
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.044
Scholarly communication0.0090.005
Open science0.0010.005
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.026
GPT teacher head0.321
Teacher spread0.295 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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